Customize your output

Overview

Dataprep supports customizability for plot(), plot_missing(), plot_correlation() and create_report(). There are mainly two settings, display and config.

1. display is a list of names which controls the Tabs, Sections and Sessions you want to show.

2. config is a dictionary that contains the customizable parameters and designated values.

For your convenience, the input for display can directly be copied from the Tabs. You can save the computations by diaplaying less contents.

And for config, we developed the how-to guide function to help you mange the frequently-use parameters. Click the question mark icon in the upper right corner of each plot, in the pop-up you will see the customizable parameters for that plot, parameters’ brief descriptions and parameters’ default settings. You can easily use the Copy All Parameters button to copy the parameters with their default settings into a dictionary. Then customize the settings and pass to the config argument.

Global and local parameter

There are two types of parameters, global and local.

1. Local parameters are plot-specified and the names are separated by .. The portion before the first . is plot name and the portion after the . is parameter name. e.g. bar.bars.

2. Global parameter applies to all the plots which has that parameter. It is single-word. e.g. ngroups .

When global and local parameter are both given, the global parameter will be overwrote by local parameters for specific plots. You can find more details about parameters in parameter_configurations.

Exmaple 1: Choose the Tabs, Sections and Sessions you want

from dataprep.eda import plot,create_report
from dataprep.datasets import load_dataset
df = load_dataset('titanic')
plot(df, 'Pclass', display=['Stats', 'Bar Chart', 'Pie Chart'])

Stats

Overview

Distinct Count	3
Unique (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Memory Size	13.9 KB
Mean	2.3086
Minimum	1
Maximum	3
Zeros	0
Zeros (%)	0.0%
Negatives	0
Negatives (%)	0.0%

Quantile Statistics

Minimum	1
5-th Percentile	1
Q1	2
Median	3
Q3	3
95-th Percentile	3
Maximum	3
Range	2
IQR	1

Descriptive Statistics

Mean	2.3086
Standard Deviation	0.8361
Variance	0.699
Sum	2057
Skewness	-0.6295
Kurtosis	-1.2796
Coefficient of Variation	0.3621

create_report(df,display=["Overview","Interactions"])

Overview

Dataset Statistics

Number of Variables	12
Number of Rows	891
Missing Cells	0
Missing Cells (%)	0.0%
Duplicate Rows	0
Duplicate Rows (%)	0.0%
Total Size in Memory	646.0 KB
Average Row Size in Memory	742.4 B

Variable Types

Categorical	12

Interactions

plot(df, display=["Stats", "Insights"])

Stats and Insights

Dataset Statistics

Number of Variables	12
Number of Rows	891
Missing Cells	177
Missing Cells (%)	1.7%
Duplicate Rows	0
Duplicate Rows (%)	0.0%
Total Size in Memory	333.9 KB
Average Row Size in Memory	383.7 B
Variable Types	Numerical: 7 Categorical: 5

Dataset Insights

PassengerId is uniformly distributed	Uniform
Age has 177 (19.87%) missing values	Missing
Survived is skewed	Skewed
Pclass is skewed	Skewed
SibSp is skewed	Skewed
Parch is skewed	Skewed
Fare is skewed	Skewed
Age has 177 (19.87%) infinite values	Infinity
Name has a high cardinality: 891 distinct values	High Cardinality
Ticket has a high cardinality: 681 distinct values	High Cardinality

Dataset Insights

Cabin has a high cardinality: 148 distinct values	High Cardinality
Name has all distinct values	Unique
Survived has 549 (61.62%) zeros	Zeros
SibSp has 608 (68.24%) zeros	Zeros
Parch has 678 (76.09%) zeros	Zeros

• 1
• 2

Example 2: Customize your plot

plot(df, "Pclass", config={'bar.bars': 10, 'bar.sort_descending': True, 'bar.yscale': 'linear', 'height': 400, 'width': 450, })

Stats Histogram KDE Plot Normal Q-Q Plot Box Plot

Overview

Distinct Count	3
Unique (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Memory Size	13.9 KB
Mean	2.3086
Minimum	1
Maximum	3
Zeros	0
Zeros (%)	0.0%
Negatives	0
Negatives (%)	0.0%

Quantile Statistics

Minimum	1
5-th Percentile	1
Q1	2
Median	3
Q3	3
95-th Percentile	3
Maximum	3
Range	2
IQR	1

Descriptive Statistics

Mean	2.3086
Standard Deviation	0.8361
Variance	0.699
Sum	2057
Skewness	-0.6295
Kurtosis	-1.2796
Coefficient of Variation	0.3621

'hist.bins': 50

Number of bins in the histogram

'hist.yscale': 'linear'

Y-axis scale ("linear" or "log")

'hist.color': '#aec7e8'

Color

'height': 400

Height of the plot

'width': 450

Width of the plot

Copy All Parameters

• Pclass is skewed left (γ1 = -0.6295)

'kde.bins': 50

Number of bins in the histogram

'kde.yscale': 'linear'

Y-axis scale ("linear" or "log")

'kde.hist_color': '#aec7e8'

Color of the density histogram

'kde.line_color': '#d62728'

Color of the density line

'height': 400

Height of the plot

'width': 450

Width of the plot

Copy All Parameters

'qqnorm.point_color': #1f77b4

Color of the points

'qqnorm.line_color': #d62728

Color of the line

'height': 400

Height of the plot

'width': 450

Width of the plot

Copy All Parameters

• Pclass is not normally distributed (p-value 7.13662382541816e-20)

'box.color': #1f77b4

Color

'height': 400

Height of the plot

'width': 450

Width of the plot

Copy All Parameters

Example 3: Customize your Insights

plot(df,config={'insight.missing.threshold':20, 'insight.duplicates.threshold':20})

Stats and Insights

Dataset Statistics

Number of Variables	12
Number of Rows	891
Missing Cells	177
Missing Cells (%)	1.7%
Duplicate Rows	0
Duplicate Rows (%)	0.0%
Total Size in Memory	333.9 KB
Average Row Size in Memory	383.7 B
Variable Types	Numerical: 7 Categorical: 5

Dataset Insights

PassengerId is uniformly distributed	Uniform
Survived is skewed	Skewed
Pclass is skewed	Skewed
SibSp is skewed	Skewed
Parch is skewed	Skewed
Fare is skewed	Skewed
Age has 177 (19.87%) infinite values	Infinity
Name has a high cardinality: 891 distinct values	High Cardinality
Ticket has a high cardinality: 681 distinct values	High Cardinality
Cabin has a high cardinality: 148 distinct values	High Cardinality

Dataset Insights

Name has all distinct values	Unique
Survived has 549 (61.62%) zeros	Zeros
SibSp has 608 (68.24%) zeros	Zeros
Parch has 678 (76.09%) zeros	Zeros

• 1
• 2

PassengerId

'hist.bins': 50

Number of bins in the histogram

'hist.yscale': 'linear'

Y-axis scale ("linear" or "log")

'hist.color': '#aec7e8'

Color

Copy All Parameters

Column Insights

1. PassengerId is uniformly distributed

Survived

'hist.bins': 50

Number of bins in the histogram

'hist.yscale': 'linear'

Y-axis scale ("linear" or "log")

'hist.color': '#aec7e8'

Color

Copy All Parameters

Column Insights

1. Survived is skewed
2. Survived has 549 (61.62%) zeros

Pclass

'hist.bins': 50

Number of bins in the histogram

'hist.yscale': 'linear'

Y-axis scale ("linear" or "log")

'hist.color': '#aec7e8'

Color

Copy All Parameters

Column Insights

1. Pclass is skewed

Name

'bar.bars': 10

Maximum number of bars to display

'bar.sort_descending': True

Whether to sort the bars in descending order

'bar.yscale': 'linear'

Y-axis scale ("linear" or "log")

Copy All Parameters

Column Insights

1. Name has a high cardinality: 891 distinct values
2. Name has all distinct values

Sex

'bar.bars': 10

Maximum number of bars to display

'bar.sort_descending': True

Whether to sort the bars in descending order

'bar.yscale': 'linear'

Y-axis scale ("linear" or "log")

Copy All Parameters

Age

'hist.bins': 50

Number of bins in the histogram

'hist.yscale': 'linear'

Y-axis scale ("linear" or "log")

'hist.color': '#aec7e8'

Color

Copy All Parameters

Column Insights

1. Age has 177 (19.87%) infinite values

SibSp

'hist.bins': 50

Number of bins in the histogram

'hist.yscale': 'linear'

Y-axis scale ("linear" or "log")

'hist.color': '#aec7e8'

Color

Copy All Parameters

Column Insights

1. SibSp is skewed
2. SibSp has 608 (68.24%) zeros

Parch

'hist.bins': 50

Number of bins in the histogram

'hist.yscale': 'linear'

Y-axis scale ("linear" or "log")

'hist.color': '#aec7e8'

Color

Copy All Parameters

Column Insights

1. Parch is skewed
2. Parch has 678 (76.09%) zeros

Ticket

'bar.bars': 10

Maximum number of bars to display

'bar.sort_descending': True

Whether to sort the bars in descending order

'bar.yscale': 'linear'

Y-axis scale ("linear" or "log")

Copy All Parameters

Column Insights

1. Ticket has a high cardinality: 681 distinct values

Fare

'hist.bins': 50

Number of bins in the histogram

'hist.yscale': 'linear'

Y-axis scale ("linear" or "log")

'hist.color': '#aec7e8'

Color

Copy All Parameters

Column Insights

1. Fare is skewed

Cabin

'bar.bars': 10

Maximum number of bars to display

'bar.sort_descending': True

Whether to sort the bars in descending order

'bar.yscale': 'linear'

Y-axis scale ("linear" or "log")

Copy All Parameters

Column Insights

1. Cabin has a high cardinality: 148 distinct values

Embarked

'bar.bars': 10

Maximum number of bars to display

'bar.sort_descending': True

Whether to sort the bars in descending order

'bar.yscale': 'linear'

Y-axis scale ("linear" or "log")

Copy All Parameters